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基于多类数据处理方法联合分析的运营桥梁安全性预警分级
Classification of Operational Bridge Safety Warning based on Joint Analysis of Multiple Data Processing Methods
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马耀华

 

( 中化学建设投资集团有限公司 ,北京 102300)

摘   要:为合理实现运营桥梁的安全性预警分级,结合去噪处理的实测数据,以累计变形序列、速率序列和加速度序列分别构建相应的预警判据,实现运营桥梁安全性预警分级的多源信息融合,充分保证分级结果的准确性。结果表明:PSO - DVMD 模型可有效剔除桥梁变形数据中的随机噪声,适用于桥梁变形数据的去噪处理;不同监测点或监测项目在不同判据条件下的预警等级存在一定差异,按不利原则综合确定桥梁的安全性预 警等级。运营桥梁安全预警分级为运营桥梁安全性评价提供了一种量化分级标准,值得进一步推广应用研究。

关键词:桥梁 ;去噪 ;安全性预警 ;相关向量机 ;趋势判断

中图分类号:U446           

文献标志码:A            

文章编号: 1005- 8249   (2024)  05- 0162- 07 

DOI:10. 19860/j.cnki.issn1005 - 8249.2024.05 .029

 

MA Yaohua

(China National Chemical Construction Investment Group Co. ,Ltd . ,  Beijing 102300 ,  China)

Abstract:In order to reasonably realize the safety early warning classification of operating bridges, based on the monitoring results of operating bridges, this paper first carries out data denoising to eliminate the noise information in the data and lay a foundation for subsequent analysis; Secondly, from three aspects of cumulative deformation sequence, velocity sequence and acceleration sequence, corresponding early warning criteria are constructed respectively to achieve multi-source information fusion of early warning classification of operational bridge safety and fully ensure the accuracy of classification results. The case analysis results show that the PSO-DVMD model can effectively eliminate the random noise in the bridge deformation data, and there are certain differences in the early warning levels of different monitoring points or monitoring items under different criteria. According to the adverse principle, the safety early warning level of the example bridge in this paper is comprehensively determined as Level II - Yellow, which belongs to the basic safety state. The follow-up monitoring should be continued, and the maintenance and reinforcement plan should be prepared. Through this study, it provides a quantitative grading standard for the safety evaluation of operating bridges, which is worthy of further popularization and application.

Keywords :  bridges;  denoising;   security early warning;  correlation vector machine;  trend judgment


作者简介: 马耀华  (1973—) , 男,本科, 高级工程师 ,研 究方向: 土木工程。

收稿日期:2023- 05- 04